Stairways Detection system which estimates distance Based on Three Connected Point and Triangular Similarity.

1. Stairways Detection and Distance
Estimation Approach Based on Three
Connected Point and Triangular Similarity
Presented By:
Md. Ahsan Habib
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2. Outline
What the Problem is!
Proposed Framework
Distance estimation
from camera to stair
Experiment Results
Conclusion
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3. According to theWorld Health Organization (WHO), about 253
million people are visually impaired.Among them, around 36 million
are blind and rest 217 million people have various vision impairment.
Among the above 80%, people are 50 years aged or above.
Those people who are visually impaired, they require more help to
navigate around the environment to avoid obstacles like stairs, path-
holes, etc.
So, “Staircase Detection and Distance Estimation” is a serious
problem for them.
What the
Problem is !
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4. Proposed
Framework
The developed system has six elementary steps.They are:
A. Gabor filter is applied to extract stair edges properly.
B. Small and non-candidate edges are eliminated.
C. Edge linking and tracking.
D. Finding ofThree connected points (TCP).
E. Increasing horizontal edge segments are extracted.
F. Detect staircase using vertical vanishing point (VP).
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5. Proposed
Framework
Cont.
Input
image
Gabor
Filtering
Edges
elimination
Edges
linking
TCP
finding
Edges
extraction
VirtualVP
calculation
Stair
region
Flow
through the
system
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6. Proposed
Framework
Gabor filter is applied to extract stair edgesA
• Gabor Filter is used to remove noise from image.
• It works on gray scale image for low computational cost.
• Canny edge detector is used to extract edges form image.Cont.
Fig. 1. (a) stair image (b) Gabor filtered image
(a) (b)
Fig. 2. (a)Canny edge image (b) horizontal edge image
(a) (b)
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7. Proposed
Framework
Small and non-candidate edges are eliminatedB
• A THRESHOLD_LINE is used to remove small and discontinuous
edges.
• The non-candidate edges also be eliminated in this stage.Cont.
Fig. 3. (a) Elimination of small edge (b) Elimination of non-candidate edge
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8. Proposed
Framework
Edge linking and trackingC
Cont.
Fig. 4. (a) Edge linking (b) Potential longest horizontal edge
• The edge linking process is applied to fill small gaps or breaks.
• Potential longest horizontal edges are kept.
(a) (b)
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9. Proposed
Framework
FindingThree Connected Point (TCP)D
Cont.
Fig. 5. (a) Procedure of calculating TCP (b) TCP in the edge image
• The beginning and ending point of each stairs step’s horizontal
edges intersect with two vertical edge points.
• Canny edge image is used to find TCP using vertical edges.
(a) (b)
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10. Proposed
Framework
Extracting increasing horizontal edge segmentsE
Cont.
• The longest increasing horizontal edge is extracted.
• This process is done using previous horizontal edge image.
• Also use TCP.
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11. Proposed
Framework
Calculating verticalVanishing Point (VP)F
Cont.
Fig. 6. (a) Longest horizontal edge segment (b) Longest increasing horizontal edge segment
(c) Estimating vertical vanishing point
• VP (imaginary) is two handrails intersection point of a staircase.
• Some stairs do not have either both handrails or one handrail.
• For these cases, two virtual handrails may construct to calculate VP.
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12. Distance
estimation
from
camera to
stair
Fig. 7. Estimating distance from the camera to stair
• Two cameras are used to measure the distance from staircase to
camera.
• A’ and B’ are the estimated points from the camera at O’ and from
camera O the estimated points are A and B.
• Here ACO and A’CO triangles are similar. By solving , 𝐷 =
𝑑
1−𝛼
Here, α is the ratio between AC and AC’.
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13. Experiment
Results
• In case of Indoor stair type, the system achieved 97.56% accuracy and
for outdoor it achieved slightly low accuracy of 96.67%.
• The system had achieved an accuracy of 97.12% on average.
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14. Experiment
Results
• The distance estimation from the camera also gives an accuracy of
98.01% on average.
Cont.
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15. Conclusion
• The developed system can detect staircase and estimate distance
from user to stair except any prior information.
• Some natural and unique properties of staircase are used to
develop this framework.
• The system had achieved an accuracy of 97.12%.
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16. AnyQuestion?
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